Elevated plasma neurofilament light was associated with multi-modal neuroimaging features in Alzheimer’s Disease signature regions and predicted future tau deposition

Background: Neurofilament Light (NfL) is a biomarker for early neurodegeneration in Alzheimer’s disease (AD). This study aims to examine the association between plasma NfL and multi-modal neuroimaging features across the AD spectrum and whether NfL predicts future tau deposition. Methods: The present study recruited 517 participants comprising Aβ negative cognitively normal (CN−) participants (n = 135), CN + participants (n = 64), individuals with mild cognitive impairment (MCI) (n = 212), and those diagnosed with AD dementia (n = 106). All the participants underwent multi-modal neuroimaging examinations. Cross-sectional and longitudinal associations between plasma NfL and multi-modal neuro-imaging features were evaluated using partial correlation analysis and linear mixed effects models. We also used linear regression analysis to investigate the association of baseline plasma NfL with future PET tau load. Mediation analysis was used to explore whether the effect of NfL on cognition was mediated by these MRI markers. Results: The results showed that baseline NfL levels and the rate of change were associated with Aβ deposition, brain atrophy, brain connectome, glucose metabolism, and brain perfusion in AD signature regions. In both Aβ positive CN and MCI participants, baseline NfL showed a significant predictive value of elevating tau burden in the left medial orbitofrontal cortex and para-hippocampus. Lastly, the multi-modal neuroimaging features mediated the association between plasma NfL and cognitive performance. Conclusions: The study supports the association between plasma NfL and multi-modal neuroimaging features in AD-vulnerable regions and its predictive value for future tau deposition.


Introduction 1.1 Understanding Alzheimer's disease and the need for biomarkers
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder and a leading cause of dementia (1).
AD is characterized by a gradual decline in cognitive function, particularly episodic memory, and it has been projected that the number of individuals aged 65 and above with AD will reach 13.8 million by 2050.
As such, there is a pressing need for early diagnosis of preclinical AD to facilitate timely intervention (2).
The current modalities utilized for tracking the progression of AD are principally reliant on imaging techniques -speci cally, volumetric magnetic resonance imaging (MRI) (3) and positron emission tomography (PET) (4) -that facilitate the visual assessment of metabolically active or aggregated Aβ and tau within the brain, as well as cerebrospinal uid (CSF) biomarkers indicative of Aβ42 and phosphorylated tau (5,6).While these imaging biomarkers are valuable, they suffer from limitations in their cost and accessibility, and CSF biomarkers necessitate invasive lumbar puncture.Thus, there is an urgent need for alternative, noninvasive, and cost-effective biomarkers capable of monitoring AD progression in a clinical context, as well as expediting the development of new therapeutic interventions.

The promise of neuro lament light chain as a biomarker for AD
The neuro lament light (NfL) chain is a promising candidate biomarker for monitoring neurodegenerative processes in AD (7,8).NfL is a component of the axonal cytoskeleton and a putative marker of largecaliber axonal degeneration, which is a critical pathological change in neurodegenerative diseases (9,10).
Previous studies have shown that NfL level and its rate of change in plasma are elevated in both sporadic and familial AD and are closely correlated with clinical symptoms and progression (8,11).Increased NfL levels have also been linked with various imaging biomarkers, including brain atrophy (hippocampal volume, entorhinal cortical thickness, ventricular volume, and temporal cortical thickness), decreased brain metabolism, and cross-sectional Aβ deposition (7,12,13,14).
However, few studies have explored the correlation between NfL and brain connectivity and perfusion, key features of AD.Furthermore, most previous studies have only focused on one or two imaging modalities.An in-depth and systematic examination of the association between plasma NfL and multi-modal neuroimaging biomarkers is still lacking.Additionally, little is known about whether plasma NfL can track AD pathology accumulation in non-demented individuals at high risk for AD.

Aims of the current study
To address these gaps in the literature, the present study aimed to investigate the potential associations between plasma NfL levels and various multi-modal imaging features, including Aβ pathology, brain atrophy, structural and functional brain connectivity, glucose metabolism, and brain perfusion.
Additionally, this study evaluated the predictive ability of baseline NfL concentrations regarding future tau deposition and tested whether the effect of NfL on cognition was mediated by these MRI markers.
Overall, this study seeks to provide a more comprehensive and systematic examination of the relationship between plasma NfL, multi-modal neuroimaging biomarkers, and cognition across the AD spectrum.By doing so, this study may contribute to a better understanding of NfL as a novel biomarker and facilitate its proper use in AD research and therapeutic trials.

ADNI database
The present article utilizes data acquired from the North American Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu).ADNI was established in 2004 by a collaboration between the National Institute on Aging, the Food and Drug Administration, private pharmaceutical companies, and not-for-pro t organizations with the aim of creating a pioneering public-private partnership.The primary objective of ADNI has been to evaluate whether the amalgamation of serial MRI, PET, other biological indicators, and clinical and neuropsychological evaluations could be used to gauge the development of MCI and early AD.The lead investigator of this enterprise is Michael W. Weiner, MD, VA Medical Center, and University of California, San Francisco.ADNI is the outcome of the concerted efforts of numerous co-investigators from an extensive range of academic institutions and private businesses, with subjects recruited from over 50 locations across the United States of America and Canada.The initial goal of ADNI was to enroll 800 subjects, yet ADNI-GO, ADNI-2, and ADNI-3 have continued the initiative.To date, these three protocols have enrolled over 1500 adults.For additional information, please visit www.adni-info.org.

Participants
In order to investigate the role of NfL across the AD spectrum, a cohort of subjects consisting of cognitively normal (CN) controls, amnestic mild cognitive impairment (aMCI), and AD patients with baseline plasma NfL data were included in this study.The inclusion and exclusion criteria have been described in detail on www.adni-info.org.Brie y, the participants were enrolled in ADNI-2 and ful lled the following criteria: aged between 55 and 90 years, completed at least 6 years of education, uent in Spanish or English, and absence of signi cant neurological disease other than AD.Controls were de ned as having Mini-Mental State Examination (MMSE) score greater than or equal to 24 and Clinical Dementia Rating scale (CDR) score of 0. Participants with aMCI had MMSE score greater than or equal to 24, objective memory loss as evidenced by scores on delayed recall on the Wechsler Memory Scale Logical Memory II, CDR 0.5, preserved activities of daily living, and absence of dementia.
The aggregation of Aβ is a hallmark pathological feature of AD, and Aβ deposits can occur in individuals who are still cognitively normal (15,16).Current research has referred to Aβ positive subjects as the preclinical phase of AD (17).Therefore, we further strati ed CN subjects into Aβ positive CN (CN+) and Aβ negative CN (CN-).Additionally, studies have shown that Aβ biomarker-positive aMCI patients are more likely to have AD pathology and are considered to be in the prodromal stage of AD compared to Aβ biomarker-negative aMCI patients(18).Therefore, only Aβ positive aMCI and AD patients were included in this study.The status of Aβ was evaluated by both cerebrospinal uid (CSF) and positron emission tomography (PET) imaging.An abnormal PET status was de ned as >0.79 standardized uptake value ratio (SUVR) using the composite reference region (19,20).A cut-off for CSF Aβ42 was de ned as CSF Aβ42<192 ng/L (21,22,23).Participants without baseline CSF Aβ42 and Aβ PET data were excluded from the study.

Measurement of plasma NfL and CSF Aβ42
The collection, processing, and storage procedures for both plasma NfL and CSF Aβ42 have been previously described on the www.adni-info.orgwebsite.The plasma NfL concentration was quanti ed utilizing the ultrasensitive Single-Molecule-Array (SIMOA) technology platform developed by Professors Henrik Zetterberg and Kaj Blennow at the University of Gothenburg, Sweden.A combination of monoclonal antibodies and puri ed bovine NfL as the calibrator was used with all samples measured in duplicate.All measurements were performed by board-certi ed laboratory technicians who remained blinded to clinical data, using a single batch of reagents.All plasma NfL samples detected were above the limit of detection, and the analytical sensitivity was less than 1pg/ml (24).The CSF concentrations of Aβ42 were measured in aliquoted samples utilizing an electrochemiluminescence immunoassay on an Elecsys Cobas-e-601 analyzer (Roche Diagnostics, Penzberg, Germany).

Neuroimaging acquisition and analysis
Detailed information describing imaging data acquisition and processing is available online at www.loni.usc.edu.

18F-orbetapir (AV-45) PET
The present study employed AV-45 PET to quantify Aβ deposition through the collection of 4 × 5-minute frames from 50 to 70 minutes after the injection of approximately 15 mCi of tracer.All scans underwent quality control checks, including assessing counts, eld-of-view, and subject movement.Subsequently, the standardized SUVR images were created by applying a series of processing steps, which included realigning and averaging the 50-70 min post-injection frames, processing the images to a standard orientation and voxel size, smoothing to a common resolution of 8 mm FWHM, and normalizing the intensity.To achieve normalization, the global cortical mean standardized uptake value ratio (SUVR), as well as the regional cortical and subcortical SUVR, were calculated using two different normalization methods (25,26).Speci cally, the global cortical mean SUVR was calculated relative to a composite reference region consisting of the whole cerebellum, brainstem/pons, and subcortical white matter (20), whereas the regional cortical and subcortical SUVR were intensity normalized to the cerebellum.Finally, regional SUVR was extracted for the standardized SUVR images using regions of interest (ROI) derived from the FreeSurfer software packages (27).

Structural MRI
The present study utilized conventional structural brain MRI scans obtained from 3-T imaging systems, employing T1-weighted images with a sagittal, volumetric magnetization-prepared rapid acquisition with gradient echo sequence.Before analysis, T1 preprocessing steps were carried out following the ADNI protocol, including correction for distortions due to gradient nonlinearity (Grad warp), intensity nonuniformity (B1), and bias eld correction (N3).Cortical and subcortical volumes were quanti ed using FreeSurfer, version 5.1, by the 2010 Desikan-Killany atlas and 2009 Destrieux atlas(28, 29).A thorough visual quality control (QC) was conducted and only images with a good overall segmentation in all 9 regions including Frontal, Temporal, Insula, Parietal, Occipital, Cerebral WM, Basal Ganglia, and Hippocampus were included.Additional information regarding the visual QC process can be found in the supplemental materials provided.Furthermore, the hippocampus is a region considered paramount in supporting episodic memory function and is extensively affected in Alzheimer's disease pathology.The hippocampus is a complex and heterogeneous region composed of various functionally and anatomically interconnected, yet distinct sub elds.Several histopathological studies have suggested differential AD-associated pathological changes among hippocampal sub elds.In order to more accurately examine the relationship between plasma NfL and hippocampal abnormality, the hippocampus was subdivided into multiple regions of interest using the automated hippocampal sub eld segmentation tool provided in FreeSurfer, version 5.1.These regions included the hippocampal tail, subiculum, CA1, CA3, CA4, the hippocampal ssure, and presubiculum (30).Supplementary Fig. 1 illustrates a sample image from a subject.

18-FluoroDeoxyGlucose PET
The measurement of glucose metabolism was conducted using 18-Fluorodeoxyglucose positron emission tomography (18F-FDG-PET) imaging.The FDG scans were collected on the same day as the AV-45 PET scans, consisting of 6 × 5-minute frames acquired from 30 to 60 minutes after injection of approximately 5mCi of tracer, and 120 minutes after injection of PIB.Subsequently, the acquired frames were realigned, averaged, reoriented, resliced to a common grid, and smoothed to a uniform resolution of 8mm.Pre-processed images were non-linearly registered to an FDG PET template in MNI (Montreal Neurological Institute) space, utilizing the "Old Normalize" tool in SPM12.Spatially normalized images were then utilized to derive standardized uptake value ratio (SUVR) maps through voxel-wise scaling to the average signal in a pons ROI (31).
To identify the most frequently observed pathological hypometabolic regions in aMCI and AD, a set of ROIs were generated based on regions commonly reported in the literature to exhibit differences between patients with AD and controls.These regions included the bilateral angular gyrus, posterior cingulate/precuneus, and inferior temporal cortex and were de ned utilizing coordinates from the Montreal Neurological Institute atlas, and merged into a single composite region (32).The average SUVR was extracted from the composite region for further analysis.
ASL data processing involved automated motion correction, aligning each ASL frame to the rst frame using a rigid body transformation, and least squares tting using SPM 8 as described previously.The difference between the mean-tagged and mean-untagged ASL images was for the perfusion-weighted images.The images were intensity scaled to account for signal decay during acquisition and to generate intensities in meaningful physiological units.ASL images were aligned to structural T1 images using FSL after geometric distortion correction.A partial volume correction was performed that assumed that CBF in gray matter is 2.5 times greater than in white matter to mitigate the effects of lower perfusion in white matter on cerebral blood ow (CBF) estimates.These images were normalized by the reference image (i.e., an estimate of blood water magnetization) to convert the signal into physical units (mL/100 g tissue/min).After, a global pass/fail rating was given based on visual inspection of signal uniformity, geometrical distortions, gray matter contrast, and the presence of large artifacts for ADNI quality control purposes.A rating of "unusable" in any of these categories resulted in a global "fail" and that participant was excluded from this study.To extract regional CBF estimates for each participant, FreeSurfer-derived anatomical ROIs were applied to CBF maps.

Diffusion tensor imaging
Diffusion tensor imaging (DTI) is a powerful tool for investigating the microstructural properties of white matter tracts.By applying measures such as fraction anisotropy (FA), mean diffusivity (MD), axial diffusion (AD), and radial diffusion (RD), it is possible to assess white matter integrity and myelination.In the present study, we utilized the JHU DTI template (33) to register each subject, with the exception of 4 ROIs that were excluded due to partial or complete out-of-eld view.In addition to the 52 JHU labels, we evaluated 5 additional ROIs, including the bilateral fornix, bilateral genu, bilateral body, and bilateral splenium of the corpus callosum, as well as the full corpus callosum, to obtain comprehensive summary measures of these regions.All ROIs were subsequently registered to the segmented atlas.Visual inspection of the images was performed to ensure adequate registration.The mean voxel value for each ROI for the maps of FA, MD, AD, and RD were obtained to analyze the data.

rs-fMRI data acquisition
All subjects were examined using a 3.0-Tesla MRI scanner, manufactured by Philips medical system.One T1-weighted image was acquired for each subject, using a pulse sequence (SPGR) with the following parameters: TR = 3000ms, TE = 30ms, matrix size = 64.0×64.0,slice thickness = 3.3mm, yielding up to 6720 slices and other valid slices.

Data preprocessing
MRI data analysis was carried out using Data Processing Assistant for Resting-State fMRI Advanced Edition (DPARSFA V5.3) (http://rfmri.org/DPARSF), based on MATLAB R2013b platform.The initial 10 volumes were discarded to eliminate the subjects' unstable and volatile magnetic eld at the beginning of the scan.All data were then realigned to correct the head motion.Reorienting functional and T1 imagines to increase the accuracy of co-registration, segmentation, and normalization.Besides segmentation, nuisance covariates regression with white matter and cerebrospinal uid, Friston 24 head motion parameters as regressors.The functional images were normalized by using T1 image uni ed segmentation.The normalized images were checked by visual inspection, and 2 subjects were excluded due to poor registration and normalization.The data were spatially smoothed (Gaussian kernel of 6 mm full width at half maximum).Then the time series were ltered with a band-pass lter (0.01-0.08 Hz).After preprocessing, 1 individual's head motion above 3mm was removed from the research.

ROI-based functional connectivity analysis
In our study, we utilized two atlases to analyze cortical and subcortical regions, namely the Destrieux atlas with 64 region parcellations (29) and the Choi atlas with 8 region parcellations, respectively.Both atlases were aligned to the Montreal Neurological Institute 5 (MNI) space and merged to create an 82region atlas.These 82 regions were used as ROIs to extract the BOLD signal time courses.Functional connectivity (FC) was then calculated by analyzing the temporal correlation of the resting-state functional magnetic resonance imaging (rs-fMRI) BOLD signal time courses across the 82 ROIs for each participant.There are different many candidates to calculate FC, such as the tangent method and partial correlation; however, we used Pearson's correlation coe cient because it is the most commonly used in previous studies.We calculated Fisher's z-transformed Pearson's correlation coe cients between the preprocessed BOLD signals of each possible pair of ROIs and used them to construct 82 × 82 symmetrical connectivity matrices in which each element represents a connection strength between 2 ROIs.In total, 4162 FC values [(82 × 82)/2] of the lower triangular matrix of the connectivity matrix were used for further analysis.

Flortaucipir (AV-1451) PET
The current study utilized Flortaucipir (AV-1451) positron emission tomography (PET) for the assessment of tau pathology.The image analysis protocol involved the acquisition of one or more Flortaucipir scans, coupled with one or more structural MRI scans, for each participant.The MRI scan that was closest in temporal proximity to each PET scan was subjected to segmentation utilizing Freesurfer software (version 7.1.1)to delineate regions of interest in the individual's native space.Subsequently, Flortaucipir scans were co-registered to their corresponding bias-corrected T1 images generated by Freesurfer, and the mean uptake of Flortaucipir in each region was computed by using the inferior cerebellar gray matter as a reference region.

Clinical and Cognitive Assessments
Among the clinical tests obtained from ADNI participants, the Alzheimer's Disease Assessment Scale Cognition 13-item scale (ADAS13) was selected for its comprehensive evaluation of global cognitive function and its established use in clinical trials of Alzheimer's disease.This instrument assesses core cognitive domains such as language, memory, praxis, and comprehension, which are relevant to AD, and is constructed from written and verbal responses.The composite score of 11 items is reported on a scale of 0 to 70, with higher scores indicating poorer cognitive function (34).To mitigate practice effects, different forms of the test were administered at each visit.

Statistical Analyses
In this study, statistical analyses were performed to evaluate various aspects of the data.Firstly, a comparison of baseline demographic and clinical characteristics by group was conducted using ANOVA and post hoc tests, or Kruskal-Wallis if the distribution data was not normal and did not satisfy the homogeneity test of variance.The rate of change in plasma NfL and differences between CN-, CN+, aMCI, and AD groups were modeled using a multivariate linear mixed effects model (LMEM) with random effects of each participant and xed effects of time from baseline.Differences in baseline plasma NfL concentration between groups were compared using analysis of covariance.Within the validation group of CN + and CN-groups, a paired sample T test was utilized to compare baseline plasma NfL concentration.In addition, the NfL cutoff to identify neurodegenerative disorders for all ages was determined as 35.02 pg/mL (90% CI) in a multicentre validation study of the diagnostic value of plasma NfL (35).The NfL concentration in each group was compared to this normal cut-off using a one-sample ttest for validation.
To accurately gauge the association between plasma NfL and multi-modal neuroimaging markers, we performed cross-sectional and longitudinal analyses.For cross-sectional analyses, partial correlation analysis was used to explore correlations between plasma NfL levels and multi-modal neuroimaging features for each diagnostic group separately.Network-Based Statistics (NBS) version 1.2(36) was used to explore correlations between functional connectivity (FC) and plasma NfL.Permutation testing with unpaired t-tests and 5000 permutations was used to determine signi cant results.False discovery rate (FDR) was used for multiple comparisons.For longitudinal analyses, LMEMs with were used to test associations of the rate of change in plasma NfL with longitudinal data on biomarkers, incorporating xed effects of time from baseline and random effect of each participant, with age, sex, and education as covariances.For FC, we calculated the change in FC and plasma NfL after 24 months as the change in rsFC and plasma NfL from the rst acquisition (baseline).NBS was used to explore correlations between the rate of change in FC and plasma NfL.
A full factorial general linear model was constructed to test the ability of baseline plasma NfL concentration to predict regional tau deposition in the brain after follow-up for 5-7 years.A mediation analysis was performed to statistically assess whether the effect of NfL on cognition was mediated by measured multi-modal brain MRI markers.The mediation analysis utilized baseline plasma NfL concentration as the predictor, multi-modal brain MRI markers as the mediator, and ADAS13 scores as the outcome variables.
All statistical analysis was performed using Matlab, IBM SPSS Statistics version 26.0, and R programming language version 4.2.1 and Matlab 9.3, R2017B.Age, sex, and education years were included as covariates in all analyses.Except for longitudinal analysis, other analyses used Bonferroni corrections for multiple comparisons, p-values < 0.05 were considered to be signi cant.

Demographic and neuropsychological data
Table 1 provides the baseline characteristics of the ADNI sample, which includes 135 CN-individuals, 64 CN + individuals, 212 individuals with aMCI, and 106 individuals with AD.No signi cant age or sex differences were found among the CN-, aMCI, and AD groups (P value>.05).However, it was observed that the CN + group was older and had a greater proportion of males than the CN-group (age: P value<.01;gender: P value<.05).The aMCI and AD groups had signi cantly lower education and MMSE scores when compared to the CN-group (Education years: aMCI versus CN-, P value<.01;AD versus CN-, P value<.001;MMSE scores: aMCI/AD versus CN-, P value<.001).Conversely, there were no signi cant differences between the CN + and CN-groups (P value>.05).Furthermore, the CSF Aβ42 and the overall mean cortical AV45 SUVR values in the CN+, aMCI, and AD groups were signi cantly higher than those in the CN-group (P value<.001)(Table .1). from LMEMs revealed that the rate of change in plasma NfL was signi cantly different between AD and CN-(P value = .0028),and between aMCI and AD (P value = .0152).No signi cant differences were detected between CN-and CN+ (P value = 1.0000), between CN-and aMCI (P value = 1.0000), between CN + and aMCI (P value = 1.0000), and between CN + and AD (p = 0.1441) (Supplementary Fig. 2).

Association between NfL and multi-modal neuroimaging features
In summary, our results show that elevated baseline concentrations of NfL are associated with Aβ deposition, brain atrophy, brain connectome, glucose metabolism, and brain perfusion in AD signature regions, including the precuneus, lateral temporal cortex, inferior parietal cortex, amygdala, entorhinal gyrus, and hippocampus in aMCI patients.Further, the longitudinal analysis shows that the change rate of NfL is related to the change rate of brain atrophy in AD-characteristic brain regions.Although this tendency was not prominent in the other groups.

Amyloid-β Pathology
In this study, all participants underwent Aβ-PET (18F-AV45 PET) at baseline.The overall mean cortical AV45 SUVR was found to be signi cantly different among the CN-, CN+, aMCI, and AD groups, with a sequential increase in uptake observed across the four groups (ANOVA and Bonferroni post hoc test; F = 449.1.P value<.001).There was no signi cant correlation between plasma NfL and overall mean cortical AV45 SUVR for any of the four groups.
However, ROI-based analysis revealed that in the aMCI group, plasma NfL concentration was associated with AV45 SUVR in widespread brain areas, particularly those that are vulnerable to AD.These areas included the bilateral medial orbitofrontal cortex, amygdala, left entorhinal cortex, lateral temporal cortex, fusiform gyrus, temporopolar cortex, para-hippocampal cortex, isthmus cingulate cortex, precuneus, and posterior cingulate cortex.Furthermore, plasma NfL in the aMCI group was also associated with AV45 SUVR in the left lingual gyrus, superior frontal gyrus, paracentral cortex, and rostral anterior cingulate cortex (Fig. 2).
In the CN-, CN+, and AD groups, no or only a few regions were found to be associated with baseline plasma NfL concentration.Speci cally, in the CN + and AD groups, no regions were associated with plasma NfL, and in the CN-group, plasma NfL was only correlated with SUVR in the left frontal pole (partial correlation P value<.05,age sex, and education years as covariates) (Fig. 3) Finally, the longitudinal analysis included 89 aMCI patients with follow-up data, and no regions were found to be associated with the rate of NfL change.

Brain Metabolism
A total of 135 CN-, 64 CN+, 210 aMCI, and 105 AD participants included in the study had FDG-PET data available.Analysis revealed a group difference in mean and maximum FDG Standard Uptake Value Ratios (SUVR) within the composite-ROI, comprising bilateral angular gyrus, posterior cingulate/precuneus, and inferior temporal cortex (mean SUVR F = 107.524,P value<.001;max SUVR F = 107.524,P value<.001).Post hoc analyses showed that AD and aMCI participants had a signi cantly higher overall uptake compared to control participants (corrected P value<.001),while no signi cant difference was observed between CN-and CN + groups (P value = .370).Notably, a signi cant correlation was found between baseline NfL levels in the aMCI group and both the mean and max meta-ROI SUVR ( P mean SUVR value = .017,r=-0.165;P max SUVR value = .024,r=-0.157) (Fig. 2).Conversely, no signi cant correlation was detected between baseline plasma NfL and the meta-ROI SUVR in the other three groups (Fig. 3).Longitudinally, there were 102 aMCI patients with the baseline and follow-up at year 2 data for longitudinal analysis.FDG SUVR in no region was found to be associated with the rate of NfL change.

Brain Perfusion
A total of 32 CN-, 11 CN+, 50 aMCI, and 24 AD participants underwent ASL imaging.Due to the limited number of ASL data in CN + individuals, they were combined with the aMCI cohort, resulting in a single group of 61 participants.Owing to the absence of ASL data in the majority of AD participants, this group was excluded from the analysis.
Partial correlation analyses revealed a signi cant positive association between baseline plasma levels of NfL and CBF in bilateral para-hippocampal regions, as well as in the left entorhinal gyrus and hippocampus, in the CN + and aMCI groups (Fig. 2).In order to verify the robustness of the ndings, we reexamined this correlation solely in the aMCI group, where similar results were obtained.Speci cally, a positive correlation trend between NfL and CBF was observed in bilateral para-hippocampal regions.By contrast, in the CN-group, the baseline plasma NfL presented a signi cant positive correlation with CBF only in the left pallidum (Fig. 3) (partial correlation P value <.05, age sex, and education years as covariates).

Brain Atrophy
The present study utilized 91 CN-, 66 CN+, 145 aMCI, and 59 AD participants with excellent overall segmentation T1-weighted images to investigate the relationship between plasma NfL and brain atrophy in AD.
The results showed that in the aMCI group, plasma NfL was primarily associated with cortical and subcortical volume in AD signature areas, including the bilateral amygdala, entorhinal gyrus, hippocampus, inferior and middle temporal gyrus, left bankssts, inferior parietal cortex, and precuneus.
These associations remained signi cant even after controlling for age, sex, and education years as covariates (Fig. 2).Interestingly, the pattern of association between plasma NfL and regional atrophy differed between aMCI and the other three groups.In the CN-group, NfL-related brain regions were mostly observed in frontal areas, with limited involvement of the temporal lobe.Speci cally, plasma NfL was correlated with the cortical volume of the left posterior cingulate, precentral, insula, right inferior temporal gyrus, and right isthmus cingulate, as well as the bilateral hippocampus and amygdala.In CN + patients, plasma NfL was correlated with the cortical volume of the left caudal anterior cingulate, frontal pole, rostral middle frontal gyrus, temporal pole, and right inferior parietal gyrus.On the other hand, in the AD group, the NfL-related brain regions were fewer and more scattered, spanning across different brain regions.In AD patients, plasma NfL was signi cantly associated with cortical volume in the right pericalcarine, middle temporal gyrus, and bilateral fusiform (Fig. 3).
Furthermore, to investigate the hippocampus in more detail, it was divided into seven subregions: the subiculum complex (anterior hippocampus), the cornu ammonis (CA) subregions comprising CA1-4 (posterior regions), the dentate gyrus (DG), and the hippocampal ssure.The partial correlation results demonstrated that plasma NfL was signi cantly correlated with cortical volume in bilateral CA1, CA2_3, CA4_DG, mbria, presubiculum, and subiculum among aMCI patients.The correlation between NfL and pre-subiculum and subiculum was particularly strong and signi cant.In contrast, the plasma NfL was signi cantly correlated with CA2_3, CA4_DG, and hippocampal ssure (Table .2).
There were 51 aMCI patients with the baseline and follow-ups at years 1 and 2 data for longitudinal analysis.Results from multivariate linear mixed effects models (LMEMs) revealed signi cant associations between the rate of change in plasma NfL and the cortical thickness average of left entorhinal, lateral occipital, middle temporal, superior temporal, and right entorhinal.

Brain connectomes
This study investigated the relationship between plasma NfL and brain connectomes by utilizing both structural and functional connectivity measures, using DTI and fMRI, respectively.In terms of structural connectivity, the study involved 35 CN-, 14 CN+, 49 aMCI, and 31 AD participants who underwent DTI examination.Due to the limited availability of DTI data for CN + participants, these individuals were combined with aMCI participants into a single group.Analysis of this combined group revealed that white matter bers associated with elevated plasma NfL levels were primarily association bers that connected different regions of the brain that are vulnerable to AD. Speci cally, plasma NfL levels were found to be signi cantly positively correlated with AD, MD, and RD values of the right cingulum, right uncinate fasciculus, and left fornix, and negatively correlated with FA values of the left cingulum and uncinate fasciculus, controlling for age, sex, and education years as covariates.To address potential confounding effects resulting from the inclusion of CN + and aMCI participants in a single group, the analysis was replicated using only aMCI patients, which yielded similar results.In contrast, analysis of AD patients revealed that elevated plasma NfL was correlated with injury in multiple projection bers, including the bilateral anterior and posterior limb of the internal capsule, corticospinal tract, and inferior cerebellar peduncle.
There were 45 aMCI patients with the baseline and follow-ups at year 1 and 2 data included in the longitudinal analysis.Results from multivariate linear mixed effects models (LMEMs) showed there were no signi cant associations between the rate of change in plasma NfL and DTI metrics.
As for functional connectivity, 62 aMCI participants had baseline resting-state fMRI data.The study found a signi cant positive correlation between plasma NfL levels and functional connectivity between the left fusiform and parstriangularis regions in the aMCI group (p FWE 2 = 0.019) (Fig. 4).Moreover, our longitudinal analysis of 37 aMCI patients with the baseline and follow-up at year 2 data demonstrated that the rate of change of functional connectivity between the left entorhinal and transverse temporal gyrus, right precuneus and right parsopercularis, as well as left inferior temporal gyrus and rostral-anterior cingulate, was signi cantly correlated with the rate of change of plasma NfL.

of Tau load by baseline NfL concentrations
A total of 50 participants diagnosed with CN + and aMCI were assessed for tau PET data.A multivariable linear regression analysis was conducted to investigate the potential predictive value of baseline plasma concentrations of NfL in relation to future tau deposition in the brain.The dependent variable for this analysis was regional tau burden after a 5 to 7 years follow-up, with baseline NfL serving as the independent predictor.Age, gender, and education years were controlled for in the analysis.The ndings revealed that baseline NfL had a signi cant effect in predicting increased tau burden in the left medial orbitofrontal cortex and para-hippocampus (F = 2.474, P value = .029,F = 2.224, P value = .042)(Fig. 5).

Mediation analysis
We further conducted a mediation analysis to investigate whether the link between plasma NfL levels and cognitive performance was mediated by multi-dimensional brain abnormalities.Speci cally, our analysis included only neuro-imaging features that exhibited a signi cant association with both baseline NfL concentration and ADAS scores.Our ndings revealed that the effect of plasma NfL on cognition was partly mediated by increased Aβ deposition and brain atrophy in the left middle temporal gyrus, as well as the inferior temporal gyrus.Furthermore, there was evidence of partial mediation by decreased mean and max glucose metabolism in a composite ROI, as well as the FA, MD, and RD value of the cingulum (see

Discussion
The concentration of NfL in blood has shown promise as a potential biomarker for the diagnosis and prognosis of AD.However, the extent to which NfL is associated with multi-modal neuroimaging features and its ability to predict future tau deposition has not been thoroughly researched.Our study aims to address these gaps by revealing the following ndings: (1) elevated baseline concentrations and change rate of NfL in individuals with aMCI were strongly associated with Aβ deposition, brain atrophy, brain connectome, glucose metabolism, and brain perfusion in AD signature regions.(2) Baseline NfL showed strong predictive value for increasing tau burden in the medial orbitofrontal cortex and para-hippocampal regions in both the CN + and the aMCI groups.
(3) The multi-modal neuro-imaging features mediated the association between plasma NfL and cognitive performance.
Plasma NfL has emerged as a promising biomarker for AD research due to its cost-effectiveness and superior tolerability compared to other biomarker measures such as MRI, PET, or CSF biomarkers.
Although previous studies have focused on the clinical utility of plasma NfL for differentiating AD and aMCI patients from controls, fewer have investigated its potential as a preclinical biomarker for early disease diagnosis.A previous study compared CN + and CN-participants and found an abnormally high concentration of plasma NfL and its rate of change (37).Our study further extends their ndings to encompass the entire AD spectrum, including CN-, CN+, Aβ positive aMCI, and Aβ positive AD groups.We found that baseline NfL concentration was higher in CN+, aMCI, and AD groups compared to the CNgroup, reinforcing the potential of NfL as a valuable biomarker for improving diagnostic and prognostic accuracy in AD patients.
The ndings of our study demonstrate a strong association between elevated baseline concentrations of NfL in individuals with aMCI and several key markers of AD, including Aβ deposition, brain atrophy, brain connectome, glucose metabolism, and brain perfusion in regions that are characteristic of AD.Additionally, changes in NfL levels were signi cantly linked to changes in brain thickness in regions characteristic of AD.The ndings of this study are consistent with previous research in this area.For instance, Yi Chen et al. found that plasma NfL levels were signi cantly elevated and related to hippocampal atrophy, larger ventricular volume, and baseline FDG SUVRs in various brain regions in aMCI group(38).Similarly, Mattsson N et al. observed a correlation between high plasma NfL and AD-related atrophy and brain hypometabolism in participants with aMCI (24).In addition, a study focused on amyloid-positive cognitively impaired individuals (clinically de ned as having aMCI or AD dementia) found that higher concentrations of plasma and cerebrospinal uid NfL were associated with hypometabolism in AD-vulnerable regions at baseline and longitudinally (39).Regarding brain structural connectivity, Nabizadeh F demonstrated a signi cant association between plasma NfL levels and disrupted WM microstructure across the brain in distinct areas (14), which overlapped with the present study's ndings.Speci cally, higher plasma NfL was related to lower FA and higher RD, AD, and MD in the fornix, uncinate fasciculus, and hippocampal cingulum.For functional connectivity, a recently published article revealed that plasma NfL was positively correlated with the deterioration of functional connectivity within the default mode network in autosomal dominant AD mutation carriers (40).
However, some studies have found results inconsistent with ours, where no cross-sectional associations were observed between NfL and any neuroimaging measures in 79 participants with aMCI (41).We suspect that this inconsistency may be due to the lack of further classi cation of aMCI, which includes simple memory impairment and memory with other impairments.In our study, we selectively included those with simple memory impairment and excluded those with negative Aβ protein, who are more likely to be in the prodromal stage of AD and re ect the characteristic changes of AD.Additionally, although previous studies found the change in plasma NfL to be associated with the change in global cognition, attention, hippocampal atrophy, and amyloid PET (41,42,43), our results only found a signi cant association between the rate of NfL change and the change in cortical atrophy in some brain region.This may be due to the limited availability of NfL data, which only covered three-time points for most patients.
Future analysis at more time points is required to reduce data bias and con rm these ndings.Furthermore, our study provides the rst evidence for the correlation between brain perfusion and plasma NfL, suggesting that reduced brain perfusion in aMCI patients may cause damage to axons of neurons, ultimately resulting in elevated NfL levels in the blood.Overall, our results support an association between plasma NfL and multi-modal neuroimaging features in AD-vulnerable regions, providing insight into NfL as a potential biomarker for tracking disease progression and facilitating its proper use in AD research and therapeutic trials.
Secondly, our study has revealed that baseline NfL levels in CN + and aMCI participants have a signi cant predictive value in elevating tau burden in the left medial orbitofrontal cortex and para-hippocampus.It is noteworthy that prior research exploring the relationship between NfL and tau pathology in AD has primarily focused on CSF, post-mortem tissue, and blood (44,45,46,47).Speci cally, studies have demonstrated that elevated NfL levels in blood are associated with increased total and phosphorylated tau levels in symptomatic carriers of an ADAD mutation and greater neuro brillary tangles in postmortem tissue of older adults with AD dementia, but not plasma tau(48).To our knowledge, only a limited number of studies have investigated the link between plasma NfL levels and PET tau in AD.Recently, one such study demonstrated that in non-demented Presenilin-1 (PSEN1) E280A mutation carriers, higher plasma NfL levels were linked to greater tau burden in regions such as the precuneus and temporal lobe, including the entorhinal cortex (49).Notably, the regions identi ed in our study differ from those found in the aforementioned research, which may be attributed to our sample consisting of individuals with autosomal-dominant AD rather than sporadic AD.Nonetheless, our research, combined with prior investigations, highlights a possible relationship between plasma NfL and aggregated neuro brillary tangles measured by [F18] FTP PET.Longitudinal data will be required to better address whether plasma NfL has the potential to be an effective predictor of downstream tau pathology.
Finally, we investigated whether the relationship between plasma levels of NfL and cognitive performance  50) reported that the effects of plasma NfL on global cognition and episodic memory in AD-spectrum patients were mediated by the functional role of several brain regions.However, these studies did not examine the mediating role of glucose metabolism, structural connectivity, and Aβ deposition.Taken together, our results point to the complex interplay between plasma NfL and multiple pathological changes that give rise to cognitive impairment in AD..
To the best of our knowledge, this represents the most extensive analysis of the correlation between NfL and other imaging biomarkers Particularly, the association between plasma NfL and brain structural, functional connectivity, and perfusion has scarcely been examined in previous studies.Through this comprehensive perspective, it is possible to gain a more profound understanding of how degeneration impacts plasma NfL concentrations.Furthermore, previous studies have primarily focused on establishing the association between NfL concentrations and imaging markers in pre-de ned regions typically affected by AD.Our analysis of the relationship between NfL concentration and multidimensional neurodegeneration markers across the entire brain enabled us to gain a greater understanding of whether the levels of NfL are driven by AD-vulnerable regional neuronal injury or agerelated neurodegeneration.Lastly, our study also examined the relationship between plasma NfL and PET tau load, which has previously been rarely explored.

Limitations and future research
The present study has certain limitations that must be acknowledged.Firstly, we acknowledge the relatively small sample size, particularly of CN + participants, in some MRI model analyses, including ASL, DTI, and brain fMRI.A larger sample size is required to better comprehend the association between plasma NfL and AD-related neuroimaging measures.Secondly, we recognize that elevated plasma NfL concentrations as a non-speci c biomarker have also been observed in other neurodegenerative diseases, such as frontotemporal dementia (51) and cerebral small vessel diseases (52).Thus, future research should include more neurodegenerative diseases to investigate the distinct roles of plasma NfL in different neurodegenerative disorders.

Conclusion
NFL is a sensitive biomarker capable of detecting the modest levels of neuronal injury associated with both the healthy aging process and other pathological neurodegenerations.Our present study supports the correlation between plasma NfL and multi-modal neuroimaging features in AD-vulnerable regions.
Furthermore, it a rms the predictive value of NFL for future tau deposition.Thus, our study underscores the potential of NFL as a preclinical biomarker for early disease diagnosis and its utility in evaluating therapeutic e cacy in clinical trials.Association of plasma NfL with ortaucipir uptake after approximately 5 to 7 years.Among the 50 Aβ+ CN and MCI participants with tau PET data available, multivariable linear regression analysis was performed to explore the predictive value of baseline plasma NfL concentrations for future tau deposition in the brain.Regional tau burden after 5 to 7 years of follow-up was used as the dependent variable and baseline NfL as a predictor, controlling for age, sex, and years of education.The baseline NfL concentration and SUVR PET uptake in the left medial orbitofrontal cortex and para-hippocampus were positively correlated (F = 2.474, p < 0.029; F = 2.224, p < 0.042).

Figures Figure 1
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Figure 2 Association
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Figure 3 Association
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Table 1
Characteristics of the study cohort All values are indicated as mean ± standard deviation except for sex.The P value in the experiment group indicates the value assessed with analyses of variance (ANOVA) among Aβ − and Aβ + CN, MCI, and AD for each variable except for sex, where a contingency chi-square test was performed with All values are indicated as mean ± standard deviation except for sex.The P value in the experiment group indicates the value assessed with analyses of variance (ANOVA) among Aβ − and Aβ + CN, MCI, and AD for each variable except for sex, where a contingency chi-square test was performed with Bonferroni corrections.The P value in the validation group indicates the value assessed with paired sample T test between CN-and CN + group.Post-hoc Bonferroni analysis provided signi cant differences between groups: a from CN−; b CN+; c MCI; d AD; *P value < .05,**P value < .01;***P value < .001Abbreviations:CN-Amyloid-beta negative cognitively normal, CN + Amyloid-beta positive cognitively normal, MCI mild cognitive impairment, AD Alzheimer's disease, MMSE mini-mental state examination; PET, positron emission tomography; CSF, cerebrospinal uid; NfL, neuro lament light.
Bonferroni corrections.The P value in the validation group indicates the value assessed with paired sample T test between CN-and CN + group.Post-hoc Bonferroni analysis provided signi cant differences between groups: a from CN−; b CN+; c MCI; d AD; *P value < .05,**P value < .01;***P value < .001Abbreviations:CN-Amyloid-beta negative cognitively normal, CN + Amyloid-beta positive cognitively normal, MCI mild cognitive impairment, AD Alzheimer's disease, MMSE mini-mental state examination; PET, positron emission tomography; CSF, cerebrospinal uid; NfL, neuro lament light.

Table 2
Association between plasma NfL and hippocampus sub elds volume.Partial correlation results showed that plasma NfL was closely related to cortical volume in bilateral CA1, CA2_3, CA4_DG, mbria, presubiculum, and subiculum in patients with MCI.The correlation between NfL and pre-subiculum and subiculum was particularly pronounced and signi cant.In CNgroup, plasma NfL was signi cantly correlated with CA2_3, CA4_DG, and hippocampal ssure in the CN-group.No correlation between plasma NfL and hippocampal subregion volume was found in the To avoid age and gender in uence on the comparison of NfL levels between the CN-and CN + groups, a validation group comprising 49 CN + individuals and 49 age, sex, and education years matched CNindividuals were enrolled.There were no signi cant differences in age, sex, education years, or MMSE scores between the CN + and CN-groups (P value>.05).However, it was observed that the CSF Aβ42 and the overall mean cortical AV45 SUVR values were higher in the CN + group than in the CN-group (P value<.001)(Table.1).3.2PlasmaNfL concentration and rate of NfL change across the AD spectrumWe rst examined the baseline concentration and rate of change of plasma NfL across the AD spectrum.Results from the multivariate analysis of covariance indicated signi cant differences in plasma NfL concentration among CN-, CN+, aMCI, and AD groups (ANOVA and Bonferroni post hoc test; F = 23.26P value<.001).The plasma NfL concentration was signi cantly elevated in CN+, aMCI, and AD groups after adjusting for age, sex, and education years.All differences remained signi cant after Bonferroni correction, except the difference between CN-and CN + groups, which was marginally signi cant (P value = .058).In the validation group, similar results were observed.The plasma NfL concentration was CN + and AD groups.The composite-ROI includes the bilateral angular gyrus, posterior cingulate/precuneus, and inferior temporal cortex Abbreviations: CA, cornuammonis; DG, dentate gyrus.CN-Amyloid-beta negative cognitively normal, CN + Amyloid-beta positive cognitively normal, MCI mild cognitive impairment, AD Alzheimer's disease.signicantlyelevated in the CN + group compared with age, sex, and education years matched CN-group (Paired t-test; P value = .014)(Fig.1).To validate the result that plasma NfL was elevated in AD progression, NfL concentration in each group was further compared to the normal NfL cutoff.Results from the one sample t-test showed that the mean NfL concentration in CN+, aMCI, and AD groups was signi cantly greater than the normal cutoff of 35.02 pg/mL.In contrast, the mean NfL concentration in CN-group was signi cantly lower than 35.02 pg/mL.Longitudinally, within-person analysis of plasma NfL dynamics (135 CN-, 64 CN+, 212 aMCI, 106 AD participants) also con rmed this elevation.Results in AD was mediated by neuroimaging features in AD signature regions.Our results demonstrated that Aβ deposition and brain atrophy in the left middle and inferior temporal gyrus, glucose metabolism in the composite region of interest, as well as the RD, MD, and FA values of the cingulum, partially mediated the association between NfL levels and cognitive function.While previous studies have established a correlation between elevated NfL concentration and poor cognitive outcomes, few have explored the underlying mechanisms that link reduced neuronal integrity, as indicated by abnormal NfL levels, to cognitive function.Our ndings are in concordance with the work of Min Su Kang et al. (37), who found that the association of NfL concentration with grey matter density was in uenced by Aβ deposits in ADvulnerable regions in Aβ + aMCI and AD.Likewise, Weina Yao et al. ( providing funds to support ADNI clinical sites in Canada.Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org).The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California.ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.